Due to the recent dangers that improvised explosive devices (IEDs) have created, much research has been performed on the detection and identification of these targets. Because of the dangers inherent in the proximity of these IEDs, the recent research trend has been to search for these targets from rapidly moving vehicles. While ground penetrating radar (GPR) and data capturing systems are getting fast enough to probe the subsurface from vehicles moving at substantial velocities, accurate automated detection and identification of targets, such as IEDs, remains a complex problem.
Because of the quantity of data involved, and the complexity of GPR data interpretation, automatic target recognition (ATR) modules are used on presently fielded systems [1][2]. These ATR modules must function in near real-time, with a low probability of false alarm. The target recognition software in present use compares the shapes and depths of objects sensed by the GPR to a database of shapes to recognize targets-of-interest. Although conventional GPR can detect lossy dielectrics, it cannot discriminate between targets of different permittivity, leading to high false alarm rates.